Growth and longevity modulation through larval environment mediate immunosenescence and immune strategy of Tenebrio molitor

Background The Disposable Soma Theory of aging suggests a trade-off between energy allocation for growth, reproduction and somatic maintenance, including immunity. While trade-offs between reproduction and immunity are well documented, those involving growth remain under-explored. Rapid growth might deplete resources, reducing investment in maintenance, potentially leading to earlier or faster senescence and a shorter lifespan. However, rapid growth could limit exposure to parasitism before reaching adulthood, decreasing immunity needs. The insect immunity’s components (cellular, enzymatic, and antibacterial) vary in cost, effectiveness, and duration. Despite overall immunity decline (immunosenescence), its components seem to age differently. We hypothesize that investment in these immune components is adjusted based on the resource cost of growth, longevity, and the associated risk of parasitism. Results We tested this hypothesis using the mealworm beetle, Tenebrio molitor as our experimental subject. By manipulating the larval environment, including three different temperatures and three relative humidity levels, we achieved a wide range of growth durations and longevities. Our main focus was on the relationship between growth duration, longevity, and specific immune components: hemocyte count, phenoloxidase activity, and antibacterial activity. We measured these immune parameters both before and after exposing the individuals to a standard bacterial immune challenge, enabling us to assess immune responses. These measurements were taken in both young and older adult beetles. Upon altering growth duration and longevity by modifying larval temperature, we observed a more pronounced investment in cellular and antibacterial defenses among individuals with slow growth and extended lifespans. Intriguingly, slower-growing and long-lived beetles exhibited reduced enzymatic activity. Similar results were found when manipulating larval growth duration and adult longevity through variations in relative humidity, with a particular focus on antibacterial activity. Conclusion The impact of growth manipulation on immune senescence varies by the specific immune parameter under consideration. Yet, in slow-growing T. molitor, a clear decline in cellular and antibacterial immune responses with age was observed. This decline can be linked to their initially stronger immune response in early life. Furthermore, our study suggests an immune strategy favoring enhanced antibacterial activity among slow-growing and long-lived T. molitor individuals. Supplementary Information The online version contains supplementary material available at 10.1186/s12979-023-00409-w.

Table S1: Best models initially including Growth duration according to ΔAIC for Cellular immunity component (approached by the coordinates on the first principal component of an ACP) the individuals grown in the different temperature conditions (Larval environment: T20, T24 and T28).The worst model is given for information.The most completed model tested contained: the Growth duration, the Age at measurement (young: ~15 days of adult stage or older: ~45 days of adult age), Challenge (before or after the immune challenge), the mass before the immune challenge, two and three variables interactions between Growth duration, Age at measurement and Challenge.Models were linear mixed models with Larval environment and Individual as random effect.

Table S2 :
Best models initially including Growth duration according to ΔAIC for Enzymatic immunity component (approached by the coordinates on the second principal component of an ACP) the individuals grown in the different temperature conditions (Larval environment: T20, T24 and T28).The worst model is given for information.The most completed model tested contained: the Growth duration, the Age at measurement (young: ~15 days of adult stage or older: ~45 days of adult age), Challenge (before or after the immune challenge), the mass before the immune challenge, two and three variables interactions between Growth duration, Age at measurement and Challenge.Models were linear mixed models with Larval environment and Individual as random effect.

Table S3 :
Best models initially including Growth duration according to ΔAIC for Antibacterial activity component (approached by the coordinates on the third principal component of an ACP) the individuals grown in the different temperature conditions (Larval environment: T20, T24 and T28).The worst model is given for information.The most completed model tested contained: the Growth duration, the Age at measurement (young: ~15 days of adult stage or older: ~45 days of adult age), Challenge (before or after the immune challenge), the mass before the immune challenge, two and three variables interactions between Growth duration, Age at measurement and Challenge.Models were linear mixed models with Larval environment and Individual as random effect.

Table S4 :
Best models initially including Adult longevity according to ΔAIC for Cellular immunity component (approached by the coordinates on the first principal component of an ACP) the individuals grown in the different temperature conditions (Larval environment: T20, T24 and T28).The worst model is given for information.The most completed model tested contained: the Adult longevity, the Age at measurement (young: ~15 days of adult stage or older: ~45 days of adult age), Challenge (before or after the immune challenge), the mass before the immune challenge, two and three variables interactions between Adult longevity, Age at measurement and Challenge.Models were linear mixed models with Larval environment and Individual as random effect.

Table S5 :
Best models initially including Adult longevity according to ΔAIC for Enzymatic immunity component (approached by the coordinates on the second principal component of an ACP) the individuals grown in the different temperature conditions (Larval environment: T20, T24 and T28).The worst model is given for information.The most completed model tested contained: the Adult longevity, the Age at measurement (young: ~15 days of adult stage or older: ~45 days of adult age), Challenge (before or after the immune challenge), the mass before the immune challenge, two and three variables interactions between Adult longevity, Age at measurement and Challenge.Models were linear mixed models with Larval environment and Individual as random effect.

Table S6 :
Best models initially including Adult longevity according to ΔAIC for Antibacterial activity component (approached by the coordinates on the third principal component of an ACP) the individuals grown in the different temperature conditions (Larval environment: T20, T24 and T28).The worst model is given for information.The most completed model tested contained: the Adult longevity, the Age at measurement (young: ~15 days of adult stage or older: ~45 days of adult age), Challenge (before or after the immune challenge), the mass before the immune challenge, two and three variables interactions between Adult longevity, Age at measurement and Challenge.Models were linear mixed models with Larval environment and Individual as random effect.

Table S7 :
Best models initially including Growth duration according to ΔAIC for Cellular immunity component (approached by the coordinates on the first principal component of an ACP) the individuals grown in the different relative humidity conditions (Larval environment: H55, H70 and H85).The worst model is given for information.The most completed model tested contained: the Growth duration, the Age at measurement (young: ~15 days of adult stage or older: ~45 days of adult age), Challenge (before or after the immune challenge), the mass before the immune challenge, two and three variables interactions between Growth duration, Age at measurement and Challenge.Models were linear mixed models with Larval environment and Individual as random effect.

Table S8 :
Best models initially including Growth duration according to ΔAIC for Enzymatic immunity component (approached by the coordinates on the second principal component of an ACP) the individuals grown in the different relative humidity conditions (Larval environment: H55, H70 and H85).The worst model is given for information.The most completed model tested contained: the Growth duration, the Age at measurement (young: ~15 days of adult stage or older: ~45 days of adult age), Challenge (before or after the immune challenge), the mass before the immune challenge, two and three variables interactions between Growth duration, Age at measurement and Challenge.Models were linear mixed models with Larval environment and Individual as random effect.

Table S9 :
Best models initially including Growth duration according to ΔAIC for Antibacterial activity component (approached by the coordinates on the third principal component of an ACP) the individuals grown in the different relative humidity conditions (Larval environment: H55, H70 and H85).The worst model is given for information.The most completed model tested contained: the Growth duration, the Age at measurement (young: ~15 days of adult stage or older: ~45 days of adult age), Challenge (before or after the immune challenge), the mass before the immune challenge, two and three variables interactions between Growth duration, Age at measurement and Challenge.Models were linear mixed models with Larval environment and Individual as random effect.

Table S10 :
Best models initially including Adult longevity according to ΔAIC for Cellular immunity component (approached by the coordinates on the first principal component of an ACP) the individuals grown in the different relative humidity conditions (Larval environment: H55, H70 and H85).The worst model is given for information.The most completed model tested contained: the Adult longevity, the Age at measurement (young: ~15 days of adult stage or older: ~45 days of adult age), Challenge (before or after the immune challenge), the mass before the immune challenge, two and three variables interactions between Adult longevity, Age at measurement and Challenge.Models were linear mixed models with Larval environment and Individual as random effect.

Table S11 :
Best models initially including Adult longevity according to ΔAIC for Enzymatic immunity component (approached by the coordinates on the second principal component of an ACP) the individuals grown in the different relative humidity conditions (Larval environment: H55, H70 and H85).The worst model is given for information.The most completed model tested contained: the Adult longevity, the Age at measurement (young: ~15 days of adult stage or older: ~45 days of adult age), Challenge (before or after the immune challenge), the mass before the immune challenge, two and three variables interactions between Adult longevity, Age at measurement and Challenge.Models were linear mixed models with Larval environment and Individual as random effect.

Table S12 :
Best models initially including Adult longevity according to ΔAIC for Antibacterial activity component (approached by the coordinates on the third principal component of an ACP) the individuals grown in the different relative humidity conditions (Larval environment: H55, H70 and H85).The worst model is given for information.The most completed model tested contained: the Adult longevity, the Age at measurement (young: ~15 days of adult stage or older: ~45 days of adult age), Challenge (before or after the immune challenge), the mass before the immune challenge, two and three variables interactions between Adult longevity, Age at measurement and Challenge.Models were linear mixed models with Larval environment and Individual as random effect.